Heuristically Driven Front Propagation for Geodesic Paths Extraction
Peyré, Gabriel; Cohen, Laurent D. (2005), Heuristically Driven Front Propagation for Geodesic Paths Extraction, in Nikos Paragios, Olivier Faugeras, Tony Chan, Christoph Schnörr, Variational, Geometric, and Level Set Methods in Computer Vision Third International Workshop, VLSM 2005, Beijing, China, October 16, 2005, Proceedings, Springer : Berlin Heidelberg, p. 173-185. 10.1007/11567646_15
TypeCommunication / Conférence
External document linkhttps://hal.archives-ouvertes.fr/hal-00365623
Book titleVariational, Geometric, and Level Set Methods in Computer Vision Third International Workshop, VLSM 2005, Beijing, China, October 16, 2005, Proceedings
Book authorNikos Paragios, Olivier Faugeras, Tony Chan, Christoph Schnörr
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Abstract (EN)In this paper we present a simple modification of the Fast Marching algorithm to speed up the computation using a heuristic. This modification leads to an algorithm that is similar in spirit to the A* algorithm used in artificial intelligence. Using a heuristic allows to extract geodesics from a single source to a single goal very quickly and with a low memory requirement. Any application that needs to compute a lot of geodesic paths can gain benefits from our algorithm. The computational saving is even more important for 3D medical images with tubular structures and for higher dimensional data.
Subjects / KeywordsGeodesic; Fast Marching; heuristic; Front Propagation
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